The Puzzle
In the late 1990s, something remarkable was happening to Australian productivity. Multi-factor productivity growth – the portion of economic growth not explained by adding more capital or labour – was running at over 2% per year. A decade later, it had collapsed to near zero, and by some measures had turned negative. What happened?
This question matters enormously for policy. Productivity growth is, in Paul Krugman's memorable phrase, "not everything, but in the long run it's almost everything." It determines living standards, fiscal sustainability, and the scope for wage growth without inflation. Yet when we try to measure it, we encounter a fundamental problem: productivity isn't directly observable. We can only infer it as a residual – the growth left over after accounting for measurable inputs.
This residual approach, pioneered by Robert Solow in 1957, has become the workhorse of productivity measurement. It has also been called "the measure of our ignorance." Understanding both its power and its limitations is essential for anyone working with macroeconomic data.